2,104+ academic papers on AI security, attacks, and defenses
Showing 821–840 of 2,104 papers
Xiaochen Zhu, Mayuri Sridhar, Srinivas Devadas
Modern machine learning models are increasingly deployed behind APIs. This renders standard weight-privatization methods (e.g. DP-SGD) unnecessarily...
Yilin Tang, Yu Wang, Lanlan Qiu +4 more
Large language models (LLMs) have shown strong capabilities in multi-step decision-making, planning and actions, and are increasingly integrated into...
Yiyang Lu, Jinwen He, Yue Zhao +2 more
Large Language Models (LLMs) are widely integrated into interactive systems such as dialogue agents and task-oriented assistants. This growing...
Rishit Chugh
The deployment of large language models (LLMs) has raised security concerns due to their susceptibility to producing harmful or policy-violating...
Jiani Liu, Yixin He, Lanlan Fan +5 more
Navigation agents powered by large language models (LLMs) convert natural language instructions into executable plans and actions. Compared to...
Fan Huang, Haewoon Kwak, Jisun An
Large Language Models (LLMs) are increasingly employed in various question-answering tasks. However, recent studies showcase that LLMs are...
HyeYoung Lee
This paper proposes a multi-agent artificial intelligence system that generates response-oriented media content in real time based on audio-derived...
Jiasen Li, Yanwei Liu, Zhuoyi Shang +2 more
Graph-structured data is foundational to numerous web applications, and watermarking is crucial for protecting their intellectual property and...
Jiayi Yuan, Jonathan Nöther, Natasha Jaques +1 more
While recent automated red-teaming methods show promise for systematically exposing model vulnerabilities, most existing approaches rely on...
Bingxin Xu, Yuzhang Shang, Binghui Wang +1 more
Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities remain...
Jonatan Rassekhnia
Post-quantum cryptography (PQC) is becoming essential for securing Internet of Things (IoT) and Industrial IoT (IIoT) systems against quantum-enabled...
Asen Dotsinski, Panagiotis Eustratiadis
As open-weight large language models (LLMs) increase in capabilities, safeguarding them against malicious prompts and understanding possible attack...
Yow-Fu Liou, Yu-Chien Tang, Yu-Hsiang Liu +1 more
Benchmarking large language models (LLMs) is critical for understanding their capabilities, limitations, and robustness. In addition to interface...
Diego Gosmar, Deborah A. Dahl
Prompt injection remains a central obstacle to the safe deployment of large language models, particularly in multi-agent settings where intermediate...
Xiaolei Zhang, Xiaojun Jia, Liquan Chen +1 more
Introducing reasoning models into Retrieval-Augmented Generation (RAG) systems enhances task performance through step-by-step reasoning, logical...
Advije Rizvani, Giovanni Apruzzese, Pavel Laskov
Large Language Models (LLMs) are increasingly adopted in the financial domain. Their exceptional capabilities to analyse textual data make them...
Anudeex Shetty, Aditya Joshi, Salil S. Kanhere
Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e., text...
Jesus-German Ortiz-Barajas, Jonathan Tonglet, Vivek Gupta +1 more
Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, enabling efficient data analysis and...
Murat Bilgehan Ertan, Emirhan Böge, Min Chen +2 more
As large language models (LLMs) are trained on increasingly opaque corpora, membership inference attacks (MIAs) have been proposed to audit whether...
Johannes Kaiser, Alexander Ziller, Eleni Triantafillou +2 more
Individual Differential Privacy (iDP) promises users control over their privacy, but this promise can be broken in practice. We reveal a previously...
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